Academic Press Library in Signal Processing
Array and Statistical Signal Processing
Description
Key Features
- Quick tutorial reviews of important and emerging topics of research in array and statistical signal processing
- Presents core principles and shows their application
- Reference content on core principles, technologies, algorithms and applications
- Comprehensive references to journal articles and other literature on which to build further, more specific and detailed knowledge
- Edited by leading people in the field who, through their reputation, have been able to commission experts to write on a particular topic
Readership
R&D engineers in signal processing and wireless and mobile communications
Table of Contents
Introduction
Signal Processing at Your Fingertips!
About the Editors
Section Editors
Section 1
Section 2
Authors Biography
Section 1: Statistical Signal Processing
Chapter 1. Introduction to Statistical Signal Processing
Acknowledgments
3.01.1 A brief historical recount
3.01.2 Content
3.01.3 Contributions
3.01.4 Suggested further reading
References
Chapter 2. Model Order Selection
Abstract
3.02.1 Introduction
3.02.2 Example: variable selection in regression
3.02.3 Methods based on statistical inference paradigms
3.02.4 Information and coding theory based methods
3.02.5 Example: estimating number of signals in subspace methods
3.02.6 Conclusion
References
Chapter 3. Non-Stationary Signal Analysis Time-Frequency Approach
Abstract
3.03.1 Introduction
3.03.2 Linear signal transforms
3.03.3 Quadratic time-frequency distributions
3.03.4 Higher order time-frequency representations
3.03.5 Processing of sparse signals in time-frequency
3.03.6 Examples of time-frequency analysis applications
References
Chapter 4. Bayesian Computational Methods in Signal Processing
Abstract
3.04.1 Introduction
3.04.2 Parameter estimation
3.04.3 Computational methods
3.04.4 State-space models and sequential inference
3.04.5 Conclusion
A Probability densities and integrals
References
Chapter 5. Distributed Signal Detection
Abstract
3.05.1 Introduction
3.05.2 Distributed detection with independent observations
3.05.3 Distributed detection with dependent observations
3.05.4 Conclusion
References
Chapter 6. Quickest Change Detection
Abstract
Acknowledgments
3.06.1 Introduction
3.06.2 Mathematical preliminaries
3.06.3 Bayesian quickest change detection
3.06.4 Minimax quickest change detection
3.06.5 Relationship between the models
3.06.6 Variants and generalizations of the quickest change detection problem
3.06.7 Applications of quickest change detection
3.06.8 Conclusions and future directions
References
Chapter 7. Geolocation—Maps, Measurements, Models, and Methods
Abstract
Acknowledgment
3.07.1 Introduction
3.07.2 Theory—overview
3.07.3 Estimation methods
3.07.4 Motion models
3.07.5 Maps and applications
3.07.6 Mapping in practice
3.07.7 Conclusion
References
Chapter 8. Performance Analysis and Bounds
Abstract
3.08.1 Introduction
3.08.2 Parametric statistical models
3.08.3 Maximum likelihood estimation and the CRB
3.08.4 Mean-square error bound
3.08.5 Perturbation methods for algorithm analysis
3.08.6 Constrained Cramér-Rao bound and constrained MLE
3.08.7 Multiplicative and non-Gaussian noise
3.08.8 Asymptotic analysis and the central limit theorem
3.08.9 Asymptotic analysis and parametric models
3.08.10 Monte Carlo methods
3.08.11 Confidence intervals
3.08.12 Conclusion
References
Chapter 9. Diffusion Adaptation Over Networks
Abstract
Acknowledgments
3.09.1 Motivation
3.09.2 Mean-square-error estimation
3.09.3 Distributed optimization via diffusion strategies
3.09.4 Adaptive diffusion strategies
3.09.5 Performance of steepest-descent diffusion strategies
3.09.6 Performance of adaptive diffusion strategies
3.09.7 Comparing the performance of cooperative strategies
3.09.8 Selecting the combination weights
3.09.9 Diffusion with noisy information exchanges
3.09.10 Extensions and further considerations
Appendices
References
Section 2: Array Signal Processing
Chapter 10. Array Signal Processing: Overview of the Included Chapters
3.10.1 Some history
3.10.2 Summary of the included chapters
3.10.3 Outlook
References
Chapter 11. Introduction to Array Processing
Abstract
3.11.1 Introduction
3.11.2 Geometric data model
3.11.3 Spatial filtering and beam patterns
3.11.4 Beam forming and signal detection
3.11.5 Direction-of-arrival estimation
3.11.6 Non-coherent array applications
3.11.7 Concluding remarks
References
Chapter 12. Adaptive and Robust Beamforming
Abstract
Acknowledgments
3.12.1 Introduction
3.12.2 Data and beamforming models
3.12.3 Adaptive beamforming
3.12.4 Robust adaptive beamforming
References
Chapter 13. Broadband Beamforming and Optimization
Abstract
3.13.1 Introduction
3.13.2 Environment and channel modeling
3.13.3 Broadband beamformer design in element space
3.13.4 Broadband beamformer design using the wave equation
3.13.5 Optimum and adaptive broadband beamforming
3.13.6 Conclusion
References
Chapter 14. DOA Estimation Methods and Algorithms
Abstract
Acknowledgments
3.14.1 Background
3.14.2 Data model
3.14.3 Beamforming methods
3.14.4 Subspace methods
3.14.5 Parametric methods
3.14.6 Wideband DOA estimation
3.14.7 Signal detection
3.14.8 Special topics
3.14.9 Discussion
References
Chapter 15. Subspace Methods and Exploitation of Special Array Structures
Abstract
Acknowledgment
3.15.1 Introduction
3.15.2 Data model
3.15.3 Subspace estimation
3.15.4 Subspace-based algorithms
3.15.5 Conclusions
References
Chapter 16. Performance Bounds and Statistical Analysis of DOA Estimation
Abstract
3.16.1 Introduction
3.16.2 Models and basic assumption
3.16.3 General statistical tools for performance analysis of DOA estimation
3.16.4 Asymptotic distribution of estimated DOA
3.16.5 Detection of number of sources
3.16.6 Resolution of two closely spaced sources
References
Chapter 17. DOA Estimation of Nonstationary Signals
Abstract
3.17.1 Introduction
3.17.2 Nonstationary signals and time-frequency representations
3.17.3 Spatial time-frequency distribution
3.17.4 DOA estimation techniques
3.17.5 Joint DOD/DOA estimation in MIMO radar systems
3.17.6 Conclusion
References
Chapter 18. Source Localization and Tracking
Abstract
3.18.1 Introduction
3.18.2 Problem formulation
3.18.3 Triangulation
3.18.4 Signal propagation models
3.18.5 Source localization algorithms
3.18.6 Target tracking algorithm
3.18.7 Conclusion
References
Chapter 19. Array Processing in the Face of Nonidealities
Abstract
3.19.1 Introduction
3.19.2 Ideal array signal models
3.19.3 Examples of array nonidealities
3.19.4 Array calibration
3.19.5 Model-driven techniques
3.19.6 Data-driven techniques
3.19.7 Robust methods
3.19.8 Array processing examples
3.19.9 Conclusion
References
Chapter 20. Applications of Array Signal Processing
Abstract
3.20.1 Introduction and background
3.20.2 Radar applications
3.20.3 Radio astronomy
3.20.4 Positioning and navigation
3.20.5 Wireless communications
3.20.6 Biomedical
3.20.7 Sonar
3.20.8 Microphone arrays
3.20.9 Chemical sensor arrays
3.20.10 Conclusion
References and Further Reading
Index
Product details
- No. of pages: 1012
- Language: English
- Copyright: © Academic Press 2013
- Published: August 31, 2013
- Imprint: Academic Press
- eBook ISBN: 9780124116214
About the Editors
Mats Viberg
Abdelhak Zoubir
About the Editors in Chief
Sergios Theodoridis
Affiliations and Expertise
Rama Chellappa
Affiliations and Expertise
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